Identifying available exercises for customizing an exercise session

ABSTRACT

System, apparatuses, and methods can provide customized exercise sessions and customized videos corresponding to the exercise session. Exercise components that are available to a user for an exercise category can be determined based on a user rank in the category and a rank of the components in the category. Certain available components can be selected to include in a customized session.

CROSS-REFERENCES TO RELATED APPLICATIONS

The present application claims priority from and is a nonprovisionalapplication of U.S. Provisional Application No. 61/800,904, entitled“Systems And Methods For Encouraging Physical Activity” filed Mar. 15,2013, the entire contents of which are herein incorporated by referencefor all purposes.

This application is related to commonly owned and concurrently filedU.S. patent application Ser. No. 14/203,392, entitled “SelectingAvailable Exercises For Customizing An Exercise Session,”; U.S. patentapplication Ser. No. 14/203,399, entitled “Generating A Custom ExerciseVideo,” and U.S. patent application Ser. No. 14/203,406, entitled“Generating Custom Audio Content For An Exercise Session,” thedisclosures of which are incorporated by reference in their entireties.

BACKGROUND

Physical activity is important to the general health of human beings.Unfortunately, this health benefit is oftentimes not enough to getpeople to commit to a routine of physical activity. People often neglectto participate in physical activity because of psychological, physical,financial, and other barriers. For instance, people may not participatein a healthy amount of physical activity because they don't have themoney to go to a gym or to hire a personal trainer, don't have time tocommit to an inflexible fitness regimen, are too embarrassed to work outin a public setting, don't find that pre-rendered (i.e. DVD-based)fitness curriculum comprehend their level of fitness or health goals, orjust generally lack motivation. Current products offer a patchwork ofsolutions to help people overcome these hurdles. However, each haveshortcomings.

One way for people to engage in physical activity is to join a gym, butthis can be costly, particularly if live classes or personal trainersessions are added. A personal trainer is expensive, and there is oftentimes no ongoing communication between the trainer and trainee betweensessions to develop an engaging regimen of physical activity for thetrainee. Additionally, people may feel embarrassed to work out in apublic setting. Further, the gym solution can be inconvenient forpeople, with problems arising that are related to scheduling,overcrowding, accessibility, and parking.

Over the years, in-home exercise solutions have popped up to combatdisadvantages related to gyms. One of these solutions is the traditionalexercise video, which the user plays on a media player in his home. Thetraditional exercise video features a pre-recording of one or morepeople instructing physical activity. The intent of this solution is forthe user to follow along with the physical activity demonstrated by thepeople shown in the video. But, these exercise videos are static anddon't change to a user's needs. Even if one had multiple videos, thevideos are still static.

Embodiments of the present invention can address these and otherproblems.

BRIEF SUMMARY

System, apparatuses, and methods can provide customized exercisesessions and customized videos corresponding to the exercise session. Inone embodiment, exercise components that are available to a user for anexercise category can be determined based on a user rank in the categoryand a rank of the components in the category. The components within arange of the user's rank or other target rank can be identified asavailable. The user's rank can be updated based on how the user performsduring an exercise, e.g., based on user feedback, such as self-reportingor sensor data. Certain available components can be selected to includein a customized session.

Other embodiments are directed to systems, portable consumer devices,and computer readable media associated with methods described herein.

A better understanding of the nature and advantages of embodiments ofthe present invention may be gained with reference to the followingdetailed description and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a flowchart illustrating a method 100 for customizing anexercise session and generating a customized video and/or audio for thesession according to embodiments of the present invention.

FIG. 2 shows a block diagram of a system 200 for generating customizedexercise sessions and videos according to embodiments of the presentinvention.

FIG. 3 shows an example fit test 300 along with results according toembodiments of the present invention.

FIG. 4 is a block diagram 400 showing a grid of user ranks and componentranks for a plurality of categories according to embodiments of thepresent invention.

FIG. 5 is a flowchart of a method 500 for updating a user rank in aparticular category according to embodiments of the present invention.

FIG. 6 shows a table 600 illustrating an update of user ranks in variouscategories according to embodiments of the present invention.

FIG. 7 is a flowchart of method 700 of customizing an exercise sessionaccording to embodiments of the present invention.

FIGS. 8A-8D illustrate the creation of an exercise session according toembodiments of the present invention.

FIG. 9 is a flowchart illustrating a method 900 of customizing anexercise session according to embodiments of the present invention.

FIG. 10 shows an example session that can be provided to a useraccording to embodiments of the present invention.

FIG. 11 is a flowchart illustrating a method 1100 of generating acustomized exercise video according to embodiments of the presentinvention.

FIG. 12 shows a user interface 1200 of a video editing program that maybe used according to embodiments of the present invention.

FIG. 13A shows a diagram for meta-tagging audio corresponding to thevideo tracks according to embodiments of the present invention. FIG. 13Bshows a diagram 1350 of different video tracks and audio tracksaccording to embodiments of the present invention.

FIG. 14A shows a diagram of a media asset 1400 that can be used tocreate a customized video according to embodiments of the presentinvention. FIG. 14B shows a diagram of the customized video 1450according to embodiments of the present invention.

FIG. 15 shows a diagram of the destination timeline 1500 including audioclips of various audio categories 1520 according to embodiments of thepresent invention.

FIG. 16 is a flowchart of a method 1600 of generating custom audiocontent for an exercise session according to embodiments of the presentinvention.

FIG. 17 shows a block diagram of an example computer system 10 usablewith system and methods according to embodiments of the presentinvention.

DEFINITIONS

A “move” corresponds an individual exercise (e.g. pushups, running,squats, yoga positions, physical therapy exercises, etc.). A move can berepeated, e.g., a push-up. Or, a move can be performed for a particularduration, e.g., time or distance, as may occur with running. A“component” corresponds to a move and an amount of activity. Forexample, the amount of activity can specific a number of reps(repetitive cycles, such as a number of push-up). The number of reps fora component can be organized into a number of sets (e.g. 2 sets of 25pushups) and other hierarchies. Different components can be of the samemove, but have a quantitative value (e.g., different number of setsand/or reps, a different time duration, different distances, differentelevations, moves per unit time, etc.).

A “category” corresponds to a particular type of exercise, e.g., thattargets a particular muscle group, skill, etc. Examples of categoriesinclude arms, legs, shoulders, back, chest, cardio, and core. Otherexamples (e.g., for yoga) can include balance, strength, andflexibility. For running, examples can include endurance, pace, andheart rate. Different sets of categories can correspond to differentcurriculums. Thus, a “curriculum” can correspond to a particular set ofcategories, and the components of those categories. A component isassigned to one or more categories. A set of components can beassociated with a category. A user can be associated with certaincategories. For example, a user can select a running curriculum, andthen the user would be associated with the set of categories for therunning curriculum.

Each component can be given a “rank” in a category associated with thecomponent. The rank can identify a level of difficulty for thecomponent. The difficulty may be the result of the amount of activityfor the component, e.g., with increasing rank for increasing activity. Auser can be given a rank for each of a plurality of categories, e.g.,those categories associated with a selected curriculum. As examples, arank can be a numerical value (e.g., integers, fractions, real numbersusing decimals) or classifications, with sublevels in any hierarchalfashion.

A “session” is composed of components to be performed during a timeperiod, e.g., in an hour. A session can include rest periods,instructions, and other segments. A session can be a complete workout. Asession can include one or more of: a video showing the components;audio giving instructions, tips, encouragement, or other audio; andmusic selections for the session. A “schedule” can correspond whatcategories are to be performed on what days as part of a session. Aschedule may or may not include the specific components to be performedon particular days. For example, a schedule could specify to work outlegs and back on one day, and chest and arms two days later.

A “program” correlates to an objective. Examples of programs can includeGet Strong, Get Moving, Get Lean, etc. A program can have one or moresession templates (also called a template). A template can specify anorganization for a session, e.g., a number of categories that must beselected, categories that are required, and time slots associated tooptional or required categories. Templates can contain other things,such as rest periods, warmups, cooldowns, other video inserts, etc. Asession template can be used for the construction of a session. Aprogram can contain session templates, scheduling rules, and other bitsfor tailoring the experience to the user.

The term “user feedback” may refer to any information obtained activelyor passively from or about a user. A user may provide answers toquestions, e.g., when creating a profile, before a session, or after asession. As another example, sensors can obtain information from a userbefore, during, or after a session. For example, a heart rate sensor canmonitor exertion during a component of a session. Example sensorsinclude FITBIT™ and JAWBONE™.

DETAILED DESCRIPTION

Embodiments may comprise systems, apparatuses, and methods for forming aportable fitness program around a user-system feedback loop so as toprovide customized sessions, as well as customized videos. Someembodiments may provide customized videos by generating and/ormanipulating video and/or audio recording of fitness content, automaticediting to form video programs featuring varying levels of fitnessdifficulty, and presenting the video to a user. A video and/or audio canbe modified in response to user feedback received from any number ofdevices and sensors. Implementations herein may be embedded into desktopcomputers, mobile devices (e.g., tablets, phones, and notebookcomputers), smart televisions, gaming consoles, streaming platforms, andother devices.

Embodiments can create infinitely customizable content easily andquickly, from just a small amount of recorded video and audio data. Inone embodiment, a trainer is simultaneously recorded performingexercises from different angles by multiple video recording devices.This method of recording video can allow the data to be manipulated toproduce customized content targeted to specific viewers based on amultitude of factors. For example, the video and audio data recorded maybe edited to produce a plurality of visually and aurally seamlesslooping iterations that may be broken down and categorized depending ontheir subject matter and degree of difficulty. This assembly ofmovement-related content can respond to user feedback, which can givesusers relatively low-cost access to the content that they need to stayengaged and motivated to achieve their fitness health goals, when theyneed it.

Embodiments can receive, normalize, and analyze data from multipledevices to customize the content that is presented to the user. Thisprocess of data collection and responsive customization of content cancreate a “feedback loop,” which allows certain embodiments to deliver afitness experience (e.g., customized sessions and videos) that adapts tothe user, rather than leaving the user bored or overworked with linearmedia experiences.

Further, embodiments can automatically push (or ease up on) the user ashis fitness level changes, rather than becoming stale or obsolete. Forexample, how a user has performed during a session can be tracked.Whether certain exercises were too difficult or too easy can bedetermined by analyzing user feedback. And, exercises in a subsequentsession can be selected based on the user feedback.

I. Overview

Embodiments can perform various functions. For example, embodiments cananalyze user feedback to determine exercise components that are suitablefor a user. For example, a user's rank within a category can be updatedbased on recent performance so that suitable components (e.g., similarlyranked components) can be identified for future sessions. Embodimentscan select components for a customized session. Embodiments can thengenerate a customized video that shows the specific selected componentsbeing performed, e.g., by combining different video tracks fromdifferent camera angles. These embodiments are described in more detailin later sections. Embodiments can also provide customized audio forsessions, such as customized vocal coaching (e.g., encouragement at aparticular time as determined from user feedback, such as sensors).

A. General Method

FIG. 1 is a flowchart illustrating a method 100 for customizing anexercise session and generating a customized video and/or audio for thesession according to embodiments of the present invention. Method 100can be performed entirely or partially by one or more computing devices,as can other methods described herein. For example, methods can beperformed by a client device (e.g., a mobile device) and/or a server,which may be in communication with the mobile device.

At block 110, user feedback is received. The user feedback can take manyforms. For example, after a user signs up, user can answer questionsabout his/her physical condition. Example questions can involve age,weight, and height. User feedback can be about a fit test that the userperforms upon initializing profile. The fit test can correspond to aninitial exercise session about which questions can be asked to the user,and answers can be received from the user as part of self-reportingdata. Other example user feedback can include information obtained fromsensors, e.g., heartbeat. Any user feedback can be obtained during orafter an exercise session.

At block 120, a model is determined. The model can correspond to afitness level of the user. The fitness level can be used to determineappropriate exercise sessions for the user. A fitness level can bedetermined for each of a plurality of different categories of exercises.Different exercises (also called moves) can also be modeled; the modelcan account for the number of repetitions and/or duration of anexercise, or other quantitative amount of an exercise, e.g., to providea rank for a component that includes the move. In one embodiment, thefitness level for particular category corresponds to a rank in thecategory, where the rank can be compared to ranks of exercisecomponents. For example, a particular curriculum can have sixcategories, and a user can be assigned a rank of how advanced the useris in each of the six categories. Examples of curriculums include aphysical therapy curriculum, a weight training curriculum, and a runningcurriculum. Curriculums can have various programs within them, e.g.,directed to different types of weight training.

At block 130, exercise components that are available to the user areselected. These exercise components can be selected based on the user'smodel in the models for the different exercise components. For example,each category for a curriculum can have components that are associatedwith that category. In a weight training curriculum, certain componentscan be associated with the chest (e.g., push-ups, bench press, etc.).Embodiments can then select appropriate (available) components for acategory from the list of all components from category based on therespective models. For instance, components that have a similar rank asa user rank in the category can be selected.

At block 140, an exercise session can be determined by selecting onlyavailable exercise components. The exercise session can provide a nameand/or description of the exercise components to be performed for agiven time period, e.g., a day, an hour, or several hours. A sessionmight include only some of the categories of an exercise program thatthe user has selected. The categories to be used for particular sessioncan be selected based on various criteria, such as the categories usedfor previous sessions.

An exercise session can be generated automatically one response torequest from a user. For example, an exercise session can be generatedat a specific time every day, every other day, or any other suitableschedule. A user might also want to generate a session, e.g., when theuser wants to add a session to schedule. The exercise session can bedetermined using various optimization techniques.

At block 150, a customized video is generated for the customizedsession. The customized video can be generated from video clips of aperson (e.g., a trainer) performing each exercise component selected forthe session. The video clips can be for a fixed amount of an exercisemove, but the video clips can be edited to provide the prescribed amountof the exercise component. The video for a particular component (e.g.,25 push-ups) can be generated from multiple video tracks, each taken ofthe trainer with a different camera at the same time. Block 150 canassemble the pre-recorded tracks and playback the video to the user.

As the amount (e.g., number of reps, elevation change, or duration)corresponding to an exercise component can vary, the video tracks arespliced together to provide the designated amount of the exercisecomponent. For example, the software might determines that the usershould do 13 pushups. However, the servers of the system might not storeany video track of exactly 13 push-ups. A video clip of 13 push-ups cangenerated from multiple video tracks that are combined at particulartime points to provide a seamless clip of 13 push-ups. The custom videocan also have custom audio, e.g., audio cues at specific times that hadbeen identified as needing extra coaching, tips, the countdown, etc. Insome embodiments, only custom audio is created. Any discussion hereinmentioning custom video can also be applied to generating custom audio.

Embodiments can repeat method 100. For example, user feedback can bedetermined about the customized session, and the user model can beupdated. The models for the components can also be updated periodically.In this manner, the customized video and sessions can continue to evolvewith the user.

B. System

FIG. 2 shows a block diagram of a system 200 for generating customizedexercise sessions and videos according to embodiments of the presentinvention. System 200 can help to trigger physical activity through theuse of generated video and data-driven feedback loops. Certainembodiments can use pre-recorded fitness content that are edited in realtime to form programs of varying difficulty levels, which can then bepresented to a user. The various modules of system 200 can reside on aclient device, a server, or a combination of both.

In one implementation, the presented content can be modified in responseto user data received from any number of devices, thereby forming auser-system feedback loop. This feedback loop and other designflexibility increases the chances of the user continuing to engage inphysical activity, as embodiments can continually produce and delivercustomized content so that the user is never burned out from beingpushed too hard, and is never bored from not being pushed enough. Thisfeedback loop and other design flexibility can also applies to physicaltherapy to help with various physical rehabilitations. The user canunderstand their progress and the feedback loop may send data back tothe therapists so that they too can monitor progress and make changes tothe program.

In FIG. 2, a user 205 can register with the software and select afitness program, e.g., one that is aligned to goals of user 205, suchgoals can include to get lean or to get strong. User 205 can interactwith an assessment module 210 to provide user data as part of userfeedback. Examples of the type of user data includes: current fitnesslevel, gender, age, height, weight, body mass index (BMI), and fitnessgoals. Assessment module 210 can interact with user 205 via any suitableuser interface, such as a keyboard, a touchscreen, or voice recognition.Assessment module 210 can provide questions to a user and receiveresponses. Assessment module 210 can evolve over time (e.g., questionsof a questionnaire can change) and can be customized to a user.Assessment module 210 can also interact with sensor devices that obtainmeasurements from a user.

The user data can be used by assessment module 220 to determine apersonal fit test for user 205. The fit test can be selected tocorrespond to an initial estimate for a fitness level of user 205. User205 can perform the fit test, and user feedback can be obtained. Suchuser feedback can include a self-assessment from 205 (e.g., too easy ortoo hard) and sensor measurements, such as heart rate or GPS data. Apurpose of the fit test can be to obtain the test results 225, which canbe used to create a more accurate model of the user's fitness level.

The information from assessment module 210 and fit test results 225 canbe fed into module 230 for determining the user model and a componentmodel. External systems 270 are shown also providing data to module 230.Such data can result from the fit test or from later exercise sessions.Module 230 can output the user's fitness level 235 in variouscategories, as is shown.

A module 240 can use the user's fitness level to determine componentsthat are available for determining an exercise session for user 205.Module 240 can also use data corresponding to difficulty rankings ofcomponents for each of the categories. Session optimizer 250 can use theavailable components and a template 245 for the program that the userhas chosen. In one embodiment, session optimizer 250 can determineexercise components to fill in time slots based on various criteria. Thedetermined session can be defined by a plurality of components in aparticular order, where certain rest periods can be part of thetemplate.

The next session can be fed into a video generator 260 that creates acustomized video corresponding to the customized accession. Videogenerator 260 can be part of or communicate with a video server 265 thatstores various video tracks to be used in generating the customizedvideo. Further details about various aspects of system 200 provided inmore detail later.

After a next session is provided to the user, additional user feedbackcan be obtained about that specific session. This session results 267can be provided to external systems 270 and module 230. Module 230 canthen update the user's fitness level and a new session and customersvideo can be generated. Session results 267 can also be used to updatethe present video, e.g., by changing a component or adding audio (e.g.,some encouragement). This feedback can provide an interactiveexperience, as opposed to a simple presentation of a one-way viewingexperience delivered to the user.

In one embodiment, video generator 260 can generate a bundle of mediaassets that are served as a file to a client device (e.g., a mobiledevice), and the client software can assemble the video from videotracks (resource files) stored on video server 265. The file sent to theclient device can include a set of instructions on how to take theresource file(s) and turn it into a sequence (final video) that can beplayed back for the user. The generation of the final video for playbackcan be done ahead of time and stored or it can be done in real time toprovide a video stream. In the former example, the video can be streamedfrom a server or played from a local file on the user device. In thelatter example, embodiments can produce a video file that is playedwithout actually ever producing the intermediary file.

In one embodiment, the video can be provided to a user's device in astream over a network (e.g., the Internet). Mobile WAN and wireless LANnetworks can be used in delivering the final video or an instructionfile for directing how a client is to put together the video tracks toobtain the final video.

II. User Feedback

As described above, embodiments can obtain user feedback in a variety ofways. This section describes some example ways for gathering userfeedback.

Certain embodiments may allow the user to sign up for a service, whichmay run on a server, for delivering customized sessions and videos. Someembodiments include a client application that can run on a laptop, TV,mobile phone, tablet, or other device using a graphical user interface(GUI). Users may then access a server application, and submit certainuser data. This user data may be inputted manually by the user, or itmay be automatically collected with the assistance of any number ofdevices.

A. Assessment

In an initial registering process, embodiments may prompt the user toanswer questions or perform certain physical tasks. An initial questioncan be about which program the user would like to select. Differentprograms can last for a different amount of time (e.g., a 7-week programor 12-week program), have different numbers of sessions per week, andthe sessions can be of different lengths. The different programs canalso have different goals, e.g., to maintain a current fitness level,increase a fitness level, muscle building, increase cardio, increaseflexibility, or other suitable goals. These examples can be composed ofmultiple programs, e.g., muscle building can include middle-of-the-roadbody building or strength building program.

Other questions can include various body metrics, which can beself-reported. Such data can include the user's age, gender, height,weight, or other data. An example question is: “How long do your typicalworkouts last?”, which can be used to determine an amount of time thatthe user wishes to allocate to exercise. The answers can be freeform(e.g., any amount of time in the last example) or be selected from alist (e.g., 15 minutes, 15-30 minutes, 30-45 minutes, or more than 45minutes). The amount of time to be allotted can be formed in multiplequestions, e.g., how many sessions per week and how many weeks.

Another question is: “how would you describe your current fitnesslevel”, which can have various categories with an increasing fitnesslevel, such as just getting started, pretty fit, athletic, and Olympic.Some questions can have multiple answers, e.g., “what's important toyou” can allow a user to select any one or more of: weight loss,improving strength, staying fit, and self-improvement.

Embodiments may then use all of the data received from the user todesignate an initial fitness level for the user. For example,embodiments may place someone who indicates that they are in greatphysical fitness into an advanced level, and thus will be presented witha program or initial fit test categorized as high difficulty. Theanalysis used to develop an initial placement designation embodied in afitness baseline may use curve fitting, load balancing, and otheradvanced methods. If used for physical therapy, the initial placementmay focus on the particular area that needs to be rehabilitated.

B. Fit Test

In an initial registering process, embodiments may prompt the user toperform an initial exercise session. The initial exercise session canspecify exercise components to be performed. The user may then view avideo corresponding to the initial session and engage in the featuredcontent-specific activity. For instance, the user may attempt to dojumping jacks at the same pace as the person of the video. The fit testcan act as a diagnostic session by providing a short workout to get abase level for the user's fitness level. Sensor data can monitor theperformance, and the user can provide explicit feedback via a userinterface.

In one embodiment, the fit test can be for running. For example, theuser can go on a run (e.g., of predetermined length, time, elevation,etc). Embodiments can provide a graphical data display (e.g., a map) toguide the user through the fit test. A customized video can include asuch a graphical data display. Customized audio can be provide alone orwith video as part of a fit test, as well as with any session.

During this process, quantitative and qualitative data may be manuallyinput by the user and/or automatically captured from Internet connecteddevices. For example, embodiments may receive data from the user'selectronic fitness wristband (among other devices) while the user isdoing jumping jacks. Additionally, during a break in between sets ofjumping jacks, the user may be prompted to report how many jumping jacksthe user completed (quantitative data), and to describe the user'ssubjective experience during the jumping jacks session, e.g. did theuser find it easy or hard to complete the exercise (qualitative data).

FIG. 3 shows an example fit test 300 along with results according toembodiments of the present invention. FIG. 3 only shows a portion of thecomponents of the fit test. More components or less components can beperformed. Each component can have an outline 310 of a person performingthe exercise component and a name 315 of the category associated withthe component. In the example shown, a name or short description 320 isprovided, along with a number of reps or duration 325. The number ofreps or duration 325 is shown as a fraction with the actual amountaccomplished in the numerator, and the denominator is the total amountthat was to be performed. Another example is a number of reps in a timeduration. A symbol 330 indicates how well the user did.

During or after the fit test, questions can be asked. The user feedbackabout the fit test can be in response to quantitative and qualitativequestions. A quantitative question can be the amount actually performed.A quantitative question can pertain to how difficult the component was.

C. User Devices

Data may be captured from any number of sensing devices before, during,or after the user's engagement in content-specific activity. The contentspecific activity can include the fit test or sessions once an exerciseprogram has begun. For example, the user may have a device that measuresthe amount and quality of sleep that he receives each night. Or, theuser may wear a device on the user's wrist, arm, leg or chest thatmeasures the user's heart rate. Or, the user may have a device that sitson the top of the user's television screen that tracks the user'sphysical movement. The sensors can measure any internal property of auser (e.g., breathing, heart rate, sleep state, etc.) and an externalproperty (e.g., amount of motion).

Embodiments can use application programming interfaces (APIs, which areprotocols intended to be used by software components to communicate witheach other) to normalize the data it receives from certain sources. Thisnormalization process can translate the received data into a form thatis consistent across sources and therefore be reliably employed. Forexample, certain electronic wristband fitness devices may measure thesame amount of physical activity differently: a wristband frommanufacturer A correctly reports the runner of a marathon as having run26.2 miles, while a wristband from manufacturer B worn by the samerunner on the same marathon race incorrectly reports a run of 25.9miles. The normalization can be based on data received from multipleusers and/or be based on specifications published by a manufacturer. TheAPIs that can correct for this discrepancy between the received datafrom wristband, giving a more accurate set of data to work with. Theaccuracy is important because certain embodiments may use such data tofurther customize the program content that is delivered to the user, asdescribed herein.

The transmission of data from the external sensor systems can bewireless (e.g., BLUETOOTH™) or wired, and can be to any user device(e.g., a phone). The gathering of data can be automatic, e.g., when thetwo devices are in proximity. The gathering of data can also be betweenclient applications on a same device, between a client application and aserver application, or be between two server applications. Communicationbetween applications can be triggered as a batch process (e.g., at aparticular time) or in response to a manual request by the user. Oncedownloaded, any pre-programmed analysis (e.g., normalization) can beperformed.

Embodiments can provide an interface for assessing and viewing all ofthe sensor data. The sensor data can be used to observe prior physicalactivity. A user can view a presentation of visually interesting charts,graphs, and tables of the sensor data.

Some sensors can monitor how a user performs during a session, e.g.,heart rate, blood oxygenation, geographical locations to determinespeed, distance, altitude, rates of elevation gain or loss, and thelike. The sensors can also relate to other physical conditions that arenot related to how a person performed during a session. For example,measurements of weight, sleep, and blood glucose can be used as part ofthe user model to determine a fitness level, and subsequent uses of thefitness level.

In one embodiment, the sensor data taken during a session can be used toupdate the session and/or video in real time. For example, a user'smotion tracking device sends a message to the client device or a serverthat the user is doing jumping jacks at an increasingly slow rate afterthe tenth jumping jack. This user feedback may be used to make changesin real time to the video. For instance, embodiments may edit thecurrently playing content on the fly (e.g., by changing a configurationfile that defines the compilation of the video stream), with the resultbeing to add the audio of a coach yelling “speed up, I'm losing you!”.The audio can be added in a seamless fashion.

As another example, the component could be ended early. And, embodimentsmay also use the feedback to change the next component shown during thecurrent session. Here, with the user tiring quickly during the jumpingjacks exercise, embodiments may choose to next show a component with alow level of difficulty following the jumping jacks, so as to nottotally exhaust and frustrate the user. Accordingly, embodiments canadapt a session to the user to maximize user progress within a session,or adapt a next session based on the feedback from the current session.

III. Ranking Model and Available Components

As described above, a user and component model module can determine afitness level for users and for components. The fitness levels arecalled a rank, and a user can have a different rank for each ofplurality of categories of a current exercise program; a component canalso have a different rank for the categories. After each session,embodiments can update the model so as you get stronger, the user modelcan change, which in turn causes more difficult sessions to be createdfor the user. In other cases, if a user has an injury or is away for awhile (fitness level may decrease), this can be observed, e.g., based onlack of usage of the software or explicit user feedback. In such a case,the user's fitness level can decrease, thereby causing easier sessionsto be crated. Thus, a user's fitness level can move in both directions,resulting in a more challenging exercise or a less challenging one.

A. Block Diagram

FIG. 4 is a block diagram 400 showing a grid of user ranks and componentranks for a plurality of categories according to embodiments of thepresent invention. Seven categories 410 are shown. For each category, aplurality of components are displayed at various difficulty levels. Thevertical axis corresponds to a difficulty rank. One user rank isdisplayed for each category.

As shown, the various components are shown associated with one of thecategories. A component may be associated with more than one category,or may just be associated with one category. The association of acomponent to a category relates to the subject matter of the component.For example, the subject matter of a component for jumping jacks may becategorized as aerobic activity (cardio), and the subject matter of acomponent featuring pushups content may be categorized as upper bodyfitness (chest).

A range is highlighted around each user rank. Components having a rankwithin the specified range of the user rank for the category can beidentified as available components for creating a session for the user.As a user can have a different rank for each category, the availablecomponents for each category can be customized to the fitness level ofthe user for the respective category.

As shown, the range of available components is centered around the userrank for a given category. For example, components within +/−50 (orother suitable value) can be identified as available components. Inother embodiments, the range can be centered around a different value.For example, if a more difficult session is desired, the range ofavailable components can be centered around a higher rank than the userhas. In a similar manner, the center of the range can be decreased ofthe less difficult session the desired (e.g., as may be desired by theuser or determined by the software).

As an example of available components, a user might have a rank of 360in the chest category. The components of the chest category can includetwo sets of eight (rank 340), two sets of ten (rank 360), and two setsof twelve (rank 375). If the allowable range is +/−20, then there arethree available pushup assignments. There may be other chest exercisesthat are also available. In one embodiment, the range could beasymmetric around the user rank.

For ease of illustration, only a few components are shown for eachcategory and for each rank. In practice, many components can exist, someof which may have a same or similar rank. And, as noted above, the userrank can be updated. Details of specifying the user rank and thecomponent ranks are provided below.

B. Rank of Components

The components may be categorized depending on its subject matter andits degree of difficulty. That is, a component can have a degree ofdifficulty within a particular category. If a component is associatedwith more than one category, the rank can differ for each category. Asfor degree of difficulty (rank), a component with a duration of fifteenseconds of jumping jacks may be categorized as low-difficulty (e.g.,rank 40), whereas two minutes of jumping jacks may be categorized ashigh-difficulty (e.g., rank 450). The categorization of the subjectmatter and degree of difficulty may be visualized in a grid, as shown inFIG. 4, in which the columns denote different subject matter(categories) and the rows represent an increasing level of difficulty.

In one embodiment, the component ranks can be set manually. For example,one military push-up can be designated a rank of 10 and twice as hard asa straight push-up (rank 5). The number of reps can then modify the rankaccording to a linear or non-linear model. In a linear model, the numberof reps can multiply the base rank for one repetition (e.g., 10 repstimes a rank 10). The number of sets can be additive in terms of rank,thereby preserving a linear model. In a nonlinear model, the addition ofmore reps can increase the difficulty more (e.g., exponentially) or less(e.g., logarithmically).

In another embodiment, new components can be ranked using ranks of knownusers. For example, new moves can be introduced into a freestyle area(e.g., a mode where a user can select components and receive a video fora predetermined reps or duration). Then, user feedback can be obtainedfrom the users. As the rank of the users is known, the component can beranked based on the user feedback and the known user rank at the time ofperforming the component. The user feedback can be used in various ways.For example, the ranks of users that marked the component as just rightcould be average. In other implementations, the number of users whomarked it as too hard or too easy can be use, e.g., to bump up or downthe average determined from those who marked it as just right.

C. Initial User Rank

As described above, a user can perform a fit test as the user's firstsession. The components of the fit test can be decided based on answersto questions. The system can then choose from a set of pre-defined fittest sessions. The ranks of the components in the selected fit test canbe used as the user's initial rank. If the selected fit test is moredifficult, the user ranks in the categories would be higher.

The results of the fit test can be used to determine whether or not toincrease or decrease the initial ranks. For example, if a user completeda component and marked it as too easy, the user's rank would increase.Alternately, the user did not complete the component and/or mark it istoo hard, the user's rank can decrease.

For example, a user's fit test contains a push-up component ranked at400, and the user completes the component and marks it as too easy.Since the user's rank is initially taken as the rank of the component(i.e., 400), the system assumes that the user and the component wereinitially matched. But, the results indicate that the user is moreadvanced. Because the initial guess equal match, the user's rank willincrease. In one implementation, the user's chest rank can be 500 afterthe fit test, as a result of a too-easy multiplier of 1.25 being appliedto the initial rank of 400. Other embodiments for updating the user rankare described in the next section.

D. Updating User Rank

The user rank can be updated periodically, e.g., after every session,every N sessions, or some period based on time. In one embodiment, theuser rank can be updated by multiplying a current rank by a simplescalar, e.g., too-easy multipliers (greater than one) or too-hardmultipliers (less than one). Other implementations can add or subtractinstead of multiply.

Other embodiments can be more complicated and utilize a comparison of apredicted (expected) outcome and an actual outcome to determine how mucha user rank changes for a given component. The changes for eachcomponent of a category can then be aggregated for that category todetermine the overall change for a user's rank. As one example, thepredicted and actual outcomes can be a win, lose, or tie. In otherimplementations, numbers can be used to indicate a degree of a win orloss. The evaluation of a win or loss is a computation calculation andis relative to an expectation, and thus can be considered to occuragainst the system's prediction.

To determine whether a win, loss, or tie has occurred, a predicted scoreis determined. Then, an actual outcome score is determined. A tiecorresponds to the two scores being the same. Thus, a ratio of 1 betweenthe two scores indicates a tie occurred. A tie would be expected if theuser's rank is equal to the component's rank. In such a case, the userrank is accurate for that particular component for that particularsession. In one embodiment, a variant of the ELO rating system is used.

FIG. 5 is a flowchart of a method 500 for updating a user rank in aparticular category according to embodiments of the present invention.Method 500 uses feedback from the user about a particular component thatwas performed. The user rank is updated based on how the user performed,and based on the user's current rank in the rank of the component wasperformed.

At block 510, a current user rank, a current component rank, and userfeedback about performance of the component are received. The componentis associated with a particular category. The user rank is alsoassociated with the same category.

At block 520, a predicted score is determined based on the user'scurrent rank in the category and the component's rank. The predictedscore is based on a difference or ratio of the two ranks. If the tworanks are equal, then the predicted score corresponds to a tie. Theexact score corresponding to a time can vary, depending on a scale thatis used. If the user's rank is higher than the component rank, thepredicted score would be that the user would do very well (e.g., ahigher score than would be expected for a tie). The higher the score,the better the expectation can be for the user to perform. For example,a user whose rank is 500 is expected to do better than user whose rankis 300 when performing a component whose rank is 200 a raw.

In one embodiment, a raw predicted score is obtained, where the rawscore is between zero and one. A transformation function can be appliedto the raw score to obtain the final predicted score. The transformationfunction can act as a normalization.

In one embodiment, the raw predicted score is determined using alogistic function, e.g.,

$E = {\frac{1}{1 + 10^{{({{R\; 1} - {R\; 2}})}/\max}}.}$raw score E is determined from the user's rank R1, the components rankR2, and the maximum rank. The majority of the raw scores center around0.5, which would correspond to a tie. Thus, the two ranks would need tohave a significant difference for a blowout to be expected. The logisticfunction is a type of sigmoid function. Other types of sigmoid functionscould be used, and other types of functions or probability distributionscan be used.

In one implementation, the zero raw scale corresponds to the user notperform in the component, and one corresponds to the user crushing thecomponent. The transformation function can take the range of the rawscore and scale it to the range used for actual outcomes. For example,the actual outcomes can have a scale between 0.4 and 1.2.

At block 530, a user score is determined based on the user feedback. Theuser score is the score of the user's actual performance. The userfeedback can include any feedback described herein, e.g., an amount ofthe component completed, the user rating (e.g., too easy or too hard),sensor data, etc. The user rating can be implemented by using adifficulty multiplier. Each factor can be given a different weight indetermining the user's score.

In one embodiment, a user score can be determined for each factor. Forexample, if the predicted heart rate is at 170 and the user's heart rateis at 170 during the workout, this would considered a tie, where a loweror higher heart rate would be a win or loss, respectively. In anotherexample, staying close to a target heart rate (e.g., +/−a cutoff) can beconsidered to be winning Losing can correspond to deviating too much ineither direction. A tie can be (for example) maintaining the desiredheart rate for 80% of the activity.

The scores for each of the factors can be a combined according to aformula to obtain a final user score. In another embodiment, method 500can be performed for each factor to obtain a change in the user's rankfor each factor. The changes can then be combined, e.g., average. Thus,there could be a score for each criteria, such that a different win/lossis determined for each one, and the total can be averaged. Or, thescores for each factor can be combined into a single score, e.g., sothat different criteria are weighted more than others.

As additional examples of factors used in determining the user score,factors such as a pace of a running component (e.g., to penalizedeviations up or down from a desired pace), the total time, incline,resistance, and a total distance can each be used. Each of the factorscan be used to determine a separate user score and then combined. Or,change a user's rank can be determined based on each of the factors, anda total change can be determined from the respective changes.

In one embodiment, the user score is determined by starting with thepercentage of completion. A rating multiplier can be used to increase ordecrease the score. Depending on certain settings, the user score can benormalized to be higher than the predicted score if the complaint iscompleted in the user with the component as just right. The settings canbe tuned in various ways.

At block 540, the predicted score is compared to the user score todetermine an outcome score. The outcome score corresponds to whether ornot the user won, lost, or tied, with varying levels of winning andlosing been possible. The comparison looks at how the user did versusexpectation to decide whether or not you won.

In one embodiment, a continuous value can be used. For example, 0.5might be a tie. Between 0.5 to 1.2 might be different levels of wins,with higher number indicating a more decisive win (e.g., doing a movevery quickly, with little effort). Differing levels of losses can havethe same behavior.

At block 550, an amount of increase or decrease is determined based onthe outcome score. As part of this determination of the amount increaseor decrease, a wager amount can be used. The wager amount can have afirst stake that can be won, and second stake that can be lost. Forinstance, if the predicted outcome was a tie, the winning and losingstakes can be the same (e.g., each 100). In another example, if thepredicted outcome is a win, the stake that can be won is less than thestake that can be lost. The same can be true if the user is expected tolose.

The stake corresponding to the outcome (e.g., win or lose) can be scaledby the degree of the win or loss. That is, a percentage of the stake isused to change the user rank. For example, the outcome score can benormalized to be a percentage. For instance, if the outcome score is adifference between the predicted score and the user score, the outcomescore can be normalized by maximum possible difference. This percentagecan then determine how much of the corresponding stake is lost, e.g., bymultiplying percentage against the stake that can be won or lost.

As a result of this wagering technique, if a user performs a componentthat is way too easy and the user obtains a strong win, the user's rankwould not increase very much. But, if the user beats a component that isway too hard, the user's rank will increase substantially. In thismanner, the right level can be achieved quicker. And the reverse is truealso. If the user is expected to have a strong win and the user loses,the decrease can be large.

FIG. 6 shows a table 600 illustrating an update of user ranks in variouscategories according to embodiments of the present invention. The firstrow 605 provides the user rank in various categories. The next 10 rowscorrespond to different components. The first column 610 shows thecategory for different components. In each row, the “user” variableidentifies the user rank. The “component” variable identifies thecomponent rank. The variable “r” corresponds to reps, and indicates thenumber of reps that were completed out of a total. A total value of zerosignifies that no reps were to be performed, e.g., the component wastime-based. The variable “s” corresponds amount of time that thecomponent was performed.

The variable “e” is the predicted/expected score. The variable “a” isthe outcome score. The variable “r” is a reward scaling. The final valuein each row corresponds to a change in the user rank. The user pointswagered (i.e., amount that can be lost) is 103. The amount that can bewon is 97. These stakes are consistent with the user having a slightlyhigher rank (rank 195) than the component (rank 190). The last row isthe user ranks in the categories after the change.

In one embodiment, if there are multiple components in a category thatare in a session (or otherwise used as part of the same update), theamount of change for each component can be averaged to obtain a totalchange for that category. For example, if a component at a gain of 50 inanother component at a loss of 25, the average would be a gain of 12.5.

E. Updating Component Ranks

In some embodiments, a rank of a component can stay constant, whereas inother embodiments, the rank may change over time. Alternatively, thecomponent ranks can be manually shifted. In other embodiments for thecomponents change, a similar method to method 500 can be used. In method500, it was assumed that the components in an accurate rank, but thatthe user rank needed to change. To update the component ranks, thereverse can be assumed, i.e., that the user ranks are accurate in thecomponent ranks need to change.

In one implementation, the updating of the component ranks can happenless frequently than the updating of the user ranks, or also beperformed on a somewhat continuous basis. For example, a user rank canbe updated after every session, and a component rank can be updated oncea month. In the update of the component ranks, the performance of manyusers for a given a component can be used to update the rank of thecomponent. For example, if many users with higher ranks were not able tosuccessfully perform a component, then the component might need toreduce in rank. Note that if a user performs a component three differenttimes with different ranks, each of those can be used as a differentdata point, each with a user rank of when the user performed thecomponent. An average amount of increase or decrease can be taken overall users for the component.

F. Confidence Multiplier

In some embodiments, a confidence multiplier can be used to change theuser rank or quickly when fewer data points are available. This mayoccur when a user first against to use the software. For example, anincrease or decrease for method 500 can be scaled by the confidencemultiplier (e.g., 1.5 to start with), thereby making the change greater.But, after the user has been using software for a long time, theconfidence multiplier can reduce towards one.

In this manner, a suitable user rank can be obtained or quickly. Theconfidence multiplier can also increase, e.g., if the user does notexercise for a while or expresses dissatisfaction with the current userrank (e.g., most things are too easy or too hard).

G. Identifying Available Components

Once a user rank is obtained and the component ranks are obtained,embodiments can select available components for use in a session. Thiscan ensure that the user is performing appropriate exercises for theuser's fitness level. As part of selecting suitable exercises, theselection of available components automatically selects the number ofreps for the duration for an exercise. This is because different numberof reps correspond to different components, and would have differentranks

FIG. 7 is a flowchart of method 700 of customizing an exercise sessionaccording to embodiments of the present invention. Method 700 can usethe user ranks and the component ranks in certain categories todetermine available components, e.g., as depicted in FIG. 4. Theavailable components can then be used to generate a customized exercisesession. Method 700 can be performed by the computer system.

At block 710, a plurality of components are identified. Each componentcorresponds to a respective physical exercise and is associated with oneof a plurality of categories. Examples of categories are providedherein. The components can correspond to all of the components of thecategories corresponding to a program selected by the user. In otherembodiments, only some of the categories are used.

At block 720, a difficulty rank is assigned to each component. Thedifficulty rank corresponds to a component rank. The difficulty rank canbe determined as described above. For example, the difficulty rank canbe assigned manually, interpolated based on a difficulty rank assignedto a particular move (e.g., rank of move multiplied by a number ofreps), or determined using method 500.

At block 730, user feedback is received from a user about physicalactivity. The user feedback can take various forms, as described herein.For example, the user feedback can be responses to a questionnaire orother assessment. Other user feedback includes a level of completion ofvarious components, and sensor data about a completion of variouscomponents.

Blocks 740 and 750 are performed for each of the plurality ofcategories.

At block 740, a category user rank for the user is determined for eachof the plurality of categories based on the user feedback. The user rankfor each of the categories can be determined via embodiments describedherein. For example, method 500 can be used. The category user ranksignifies that the user has a particular rank in the category, and thatthe rank corresponds to a particular user.

At block 750, a respective set of components having a difficulty rankwithin a specified range of the category user rank is identified asbeing available to determine an exercise session. The range can be asshown in FIG. 4. As described for FIG. 4, the range can be centered atthe category user rank or centered at a value that is offset from thecategory user rank. For example, the system can determine (or the usercan request) that an easier or more difficult session be created.

At block 760, the identified sets of components are used to create anexercise session composed of a plurality of available components. Theselection of which available components to use is described in moredetail below.

At block 770, the exercise session is provided to the user. The exercisesession can be provided in various ways. For example, the exercisesession can be displayed to the user via a client application, e.g., aclient application and a user interface that the user has providedfeedback. Method 700 can be performed by server computer, which can sendthe exercise session to a client device. As a result of using ranks,embodiments may assemble a video containing an advanced arms workout anda beginner's legs workout, when the user has a higher rank in the armscategory and a lower rank in the legs category.

In one embodiment, the components can be created for a particular userrank. For example, if a user's rank is 400 and a single repetition moveis 40, then a component of a set of 10 can be created. Similarly, a moveof a particular time duration (e.g., 1 minute of running) might have arank of 40, and a component with a 10 minute duration can be created.Such embodiments still fall within method 700 as a rank is assigned tothe components.

IV. Determining Session

Once the available components are identified, the available componentscan be used to create an exercise session. The exercise session includesa plurality of components and can be organized into a particular order.For example, the components of the session can be assigned to aparticular slot, e.g., slots numbered 1 to 10 when the session has beencomponents. Various criteria can be used to determine which componentsto select for an exercise session. For example, components can beassembled to support a limitless number of fitness goals includingweight loss, strength gains, or programs for busy lifestyles.

An exercise session can correspond to a particular time period, e.g.,one day, one hour, or several hours. In one embodiment, more than oneexercise session can be determined at a same time. In this manner, theschedule of exercise sessions can be determined as part of a singleoptimization process. Since the results of one exercise session canimpact the next exercise session, embodiments can generate one sessionat time and use the results of previous exercise sessions. Embodimentscan also generate many sessions as per the schedule, and then update anylater exercise sessions after one or more earlier exercise sessions areperformed.

In some implementations, a user can manually request a generation of anexercise session, e.g., by specifying availability or other parameters.Exercise sessions can also be generated at specified times, e.g., atmidnight the day before the exercise session is to be performed.

A. Block Diagram

FIGS. 8A-8D illustrate the creation of an exercise session according toembodiments of the present invention. In one embodiment, the creation ofthe exercise session can use available components identified by method700.

FIG. 8A shows a plurality of available components. Components of thesame category are highlighted in a same color (shading). The number ofcomponents is only representative, and is limited for ease ofillustration. Components 810 a correspond to one category (category A),components 810 b correspond to another category (category B), andcomponents 810 c correspond to a third category (category C). Asexamples, category A can be chest, category B can be arms, and categoryC can be cardio.

The number of different categories can be defined based on a selectedprogram. For example, if a user selected a get strong weight trainingprogram, then the available components of a first set of categories maybe used. But, if the user selected a get fit running program, then theavailable components of the second set of categories may be used.

FIG. 8B shows a plurality of session templates for a given program. Atthe time of registering, the user can select a program, as is describedherein. A program may have multiple templates. A template can definecertain properties of the session. For example, a template can specifywhen rests are to be taken and the number of categories from whichcomponents are to be selected for creating a session. For instance, arest can be taken after every four components. The template can alsoassign timeslots two different categories, as is described in moredetail below. Thus, each of the four session templates can have adifferent structure.

In the example shown, session template 820 is selected. The selection ofa session template can be based on various criteria. For example, a usermay select a preferred template from among a display of multipletemplates. If a user does not select a template for a next sessions buthas selected templates in the past, embodiments could choose a templateused least frequently in the recent set of sessions.

The templates could alternate every N sessions, e.g., use one templatefor 2 sessions, a next template for the next 2 sessions, and so on untilall sessions have been used, and then the process can repeat. Aparticular program can specify different templates to be used atdifferent times in the program. For example, a program can be 8 weekslong, and each template can be used for two weeks before the nexttemplate is used. Other embodiments can select a template at random,e.g., to avoid complacency, to provide uniform coverage of templates, toprovide a rigorous schedule (“hell week”) at certain times, and toemphasize categories that a person has a lower rank.

FIG. 8C shows the selected session template 820 and selected categories830 a-830 c, which correspond to sets of components 810 a-810 c. Theselection of the categories can be restricted by the selected template,which can specify the number of categories to be used. In this example,session template 820 specifies that three categories are to be used. Inone embodiment, the user can specify categories or other criteria (e.g.,categories not to use), while other embodiments can have an automatedprocess. In various embodiments, the automated process can useconditional logic to determine a result based on various criteria andcan use an optimization process.

The selection of the categories can be based on various criteria, suchas categories used in previous sessions, a preference for certaincategories to be grouped together, and any preference within a programto emphasize certain categories over other categories. For example, ifthe session of yesterday used categories D and E, then there might be apreference not to use those categories.

In one embodiment, each category can be assigned a score, e.g., based oncriteria described herein. A higher score can designate a higherpreference for that category. A first category can then be selectedbased on the relative preferences. For example, a higher probability ofselection can correspond to a higher score. Once a first categoryselected, new scores can be assigned for the remaining categories, whichmay allow a preference for certain categories to be used in a samesession.

Besides having preferences for certain categories, certain categoriescan be excluded or have a reduced score, e.g., as the user might haveindicated an injury for a body part corresponding to a particularcategory. Other constraints can include that two categories must be usedtogether.

FIG. 8D shows a selection of components to fill in the selectedtemplate. The left panel of FIG. 8D shows an expanded view of sessiontemplate 820. As shown, session template 820 has 16 timeslots 840. Eachtime slot is to be assigned a particular component of a particularcategory. In this example, the first two timeslots 841 and 842 aredesignated for cardio. Thus, certain timeslots of a template can berequired to have a specific category, and other time slots can allowselection. The third time slot 843 corresponds to a first category, andis marked with an “A”. Other timeslots that are required to have thesame category can be marked with the same label, as is shown. The fourthtime slot 844 corresponds to a second category, as marked with a “B”. Arest period exists between blocks of four components. Other templatescan have a different organization structure.

The right panel of FIG. 8D shows a final session 850. The timeslots areshown filled with available components. In this example, category 830 awas selected to correspond to timeslots marked with “A” in sessiontemplate 820. Category 830 b was selected to correspond to timeslotsmarked with “B” in session template 820. Once certain categories areassigned to certain timeslots, specific components from the designatedcategories can be selected.

The selection of which components to use from the selected category canbe based on various criteria, such as components used in previoussessions, the aggregate component score of the selected components, anda target difficulty for the session. In one embodiment, a targetdifficulty rank can be designated for particular category. As examples,the target difficulty rank can be the user rank or an offset from theuser rank, where the offset increases or decreases the difficulty.Examples of when the target is offset from the user rank include whenthe user did not sleep well (e.g., as determined by sensor data) or theuser has not had a hard session in a while (or too many easy ones) orfor plateau busting. The offset can change which components areavailable, e.g., by shifting the range upward or downward in FIG. 4. Theamount of offset can be predetermined (e.g., only 25 above or below) orallowed to vary.

The selected components can be chosen to have an average rank that aresufficiently close to the target difficulty rank (e.g., +/−5 or othercutoff or threshold value). The selection of the components to provide adesired average can be performed in various ways. For example, onecomponent can be chosen and if the component is below the target then anext selected component can be above the target. A brute force methodcould try various permutations of components until one is within acutoff of the target rank. If the average is too high, then the highestranked component can be dropped and another selected. A similar processcan be done if the average is too low.

In one implementation, the components are selected without regard toorder. Thus, in this example, four components of category 830 a can beselected for including into session 850. These four selected componentscan be randomly assigned to any corresponding time slot. In anotherimplementation, a particular component can be selected for a particulartimeslot.

There can be a preference for not choosing a same component twice fortwo slots of a session. However, if there are not a sufficient number ofcomponents (e.g., only 3 available components in a selected category),or if other components have a low preference or have been excluded, thena same component can be assigned to more than one time slot. As withselecting categories, a preference score can be assigned to eachcomponent based on user's preference, components used in previoussessions, a preference for variety, and other suitable criteria. The topcomponents can be searched first to see if their average can satisfy thetarget rank.

B. Method

FIG. 9 is a flowchart illustrating a method 900 of customizing anexercise session according to embodiments of the present invention.Method 900 can use the available components determined and method 700.Method 900 can also use the user ranks and the component ranks incertain categories. Method 900 can be performed by the computer system.

At block 910, a set of available components is received for a pluralityof categories. Each component corresponds to a respective physicalexercise, and each available component has a rank for a correspondingcategory. The number of categories can correspond to a program selectedby the user. Aspects of the components and ranks are described above.

At block 920, a selection of a session template is received. A sessiontemplate specifies a number of categories. For example, the sessiontemplate can specify that three categories are to be used. The sessiontemplate can also require one or more specific categories (e.g.,cardio). The session template can specify a number of slots forcomponents for each category. For example, the session template canspecify that for slots are to be used for a first category that is to benamed later. Further examples are described above for FIG. 8.

At block 930, a group of categories is selected consistent with thesession template. For example, if the session template specifies that afirst category is required and that two other categories are needed, thegroup of categories includes the first category and two othercategories. Various criteria can be used to select the categories thatare not required. Example criteria include categories used in previoussessions, a preference to use one category with another category, userpreferences, and other suitable criteria. Other example criteria aredescribed herein.

Blocks 940 and 950 are performed for each of the selected categories.

At block 940, components are selected from available components for eachof the selected categories. The selected components for particularcategory can have ranks that satisfy one or more criteria with respectto a rank of the user. One example criterion is that the average rank ofthe selected components is within a cutoff of a target value (e.g., theuser rank or an offset from the user rank).

At block 950, the selected components are placed in the slots of thesession template. The slots can be ordered or not ordered. Inembodiments where the slots are not ordered, the selected components fora particular category can be placed into any slot. In embodiments wherethe slots are ordered, the components can still be placed into any slotor a component can be selected for placement into a particular slot. Theselection of the component for a particular ordered slot can be based onvarious criteria, e.g., to ensure that to higher rank components are notplaced back-to-back.

At block 960, a session is created from the selected components at theslots of the session template. The session can include other itemsbesides the selected components. The session can include specific restperiods. The session can include other information to be provided, suchas a description of each of the components. A session can also includevideo content, as is described in more detail below.

At block 970, the exercise session is provided to the user. The exercisesession can be provided in various ways. For example, the exercisesession can be displayed to the user via a client application, e.g., aclient application and a user interface that the user has providedfeedback. Thus, a user device can create the exercise session andprovide it to the user. In another embodiment, a server system createsthe session. Thus, method 900 can be performed by server computer, whichcan send the exercise session to a user device.

FIG. 10 shows an example session that can be provided to a useraccording to embodiments of the present invention. All components areshown, which may be all or only a portion of the session. Each componentas a name or short description. Each component also has a number of repsor time that the component is to be performed.

C. Criteria

As described above, various criteria can be used for the selection of acategory and the selection of components within a category. This sectiondescribes other criteria that may be used in addition to the criteriadescribed in other sections.

In one embodiment, the ordering of the components in a session can bedetermined based on various criteria. For example, two components maypreferentially be performed in sequence, or constraints can specificallyprohibit or discourage two components from being performed in sequence.One instance is where a component belong to a first category, but has asubcategory (e.g., minor involvement of a different body group). Then,the component would generally not be not in succession with a componentfrom the subcategory. For example, a first back exercise component canalso engage legs, and thus the algorithm for selecting the order doesnot include a legs component after the first back exercise component.

The order of the components can also impact which components areselected. In such an embodiment, a score can be assigned to the order ofcomponents for a possible session. The score can be analyzed todetermine if it is acceptable (e.g., too low). If the score is notacceptable, different components can be selected. A lower score can becaused by two components that should not be performed in sequence. Or, alower score can result from multiple components in sequence that have ahigher rank than the target rank.

Other criteria can include how long are your workouts going to be and apreference for complexity of sessions (e.g., how many categories ordifferent components are desired). One embodiment can use alternate axisfor selection of components. For example, one yoga session may revolvearound “hip flexibility” which might be a category. Another session mayfocus on “relaxation”, which could pull components (e.g., still withinyour range of user rank) from all categories as long as the componentsare tagged as “relaxation”.

V. Generating Customized Video

In certain embodiments, a customized video can be generated thatcorresponds to a session. In one implementation, video and audio datarecorded during a content production process may be edited to produce aplurality of visually and aurally seamless looping iterations that maybe broken down and categorized depending on their subject matter anddegree of difficulty. This assembly of fully customizable, targetableexercise or other movement-related content can respond to user data,which gives users relatively low-cost access to the content that theyneed to stay engaged and motivated to achieve their fitness healthgoals, when they need it.

The recorded video and audio data can be captured in a manner thatallows it to be manipulated to produce content that may be customized(e.g., in real time) and targeted to specific viewers based on amultitude of factors, including data received from the user and theuser's devices. As an example of a customized video, one user may need aprogram depicting 15 pushups, while another user may need a programdepicting 50 pushups. Both videos can be created from the same recordedvideo. This same customization can span over the course of an entirecurriculum.

A. Intro

The video and audio data recorded and or generated during a contentproduction process described above may be manipulated to produce aninfinite number of visually and aurally seamless customized videoscorresponding to customized sessions. The process can be referred to as“atomization,” and the product of which can be referred to as an“atomized video” (or atomized program).

Consider the example of a trainer/coach recorded doing jumping jacks,for a duration of thirty seconds. By atomizing the footage from multiplecameras, many iterations of video and audio content (Atomized videos)can be produced that appear to show the trainer seamlessly performingjumping jacks for one minute, three minutes, thirty minutes, or otherperiods of time. Such atomized videos would not simply slow down orspeed up the footage to fit these amounts of time; rather, they can beedited and looped in a way such that a different number of jumping jackswould be shown, depending on the length of the video.

The atomization process can utilize decision points within various videotracks. For example, multiple cameras can be used to obtain variousvideo clips (tracks) of the trainer performing an exercise move. Thevideo tracks can be analyzed to identify decision points within thetracks. These decision points can be used to switch between video tracksso as to provide the desired amount of exercise motion in the video.

B. Method

FIG. 11 is a flowchart illustrating a method 1100 of generating acustomized exercise video according to embodiments of the presentinvention. Method 1100 can be used for preparing a video of a particularamount of a move. For example, the amount may be total number of reps ortotal amount of time that the move is displayed. The move is repetitive,and thus the video can appear seamless when a proper combination ofmultiple video clips is performed. Method 1100 can be performed by acomputer system, such as a server or client device, as can other methodsdescribed herein.

At block 1110, data of a plurality of video tracks of repetitive motionof a person is received. For example, a person may be performingpush-ups. Each video track can correspond to a different camera used tocapture the repetitive motion of the person. The various cameras can beat fixed position or moving, or combination of both. The data can beorganized in any suitable fashion. The data may also include audiotracks, as is described in more detail below.

At block 1120, metadata corresponding to the plurality of video tracksis received. The metadata can be obtained from a prior processing of thevideo tracks and then received by a computer system. In anotherembodiment, the computer system can process the video tracks todetermine the metadata. Processing the video tracks is described in moredetail in sections below. In some embodiments, the video tracksthemselves are not needed and only the metadata and other data may beused.

The metadata includes times of decision points in the repetitive motionfor each video track. The decision points can correspond to times thatthe final video can switch from one video track and the video track. Anexample decision point is the end of an intro section. For example, thetrainer in the video can introduce the move, which may include a shortdescription and a sample video excerpt of one rep. Another decisionpoint can be a particular position in the rep. For example, the top orbottom (or both) points in a push-up. The decision points can allow thevideo tracks to be synchronized.

At block 1130, at each of a plurality of the decision points, a segmentof one of the video tracks is selected to use for a next segment of theexercise video based on one or more selection rules. For example, adecision point can be the beginning of each video track. At thisdecision point, one of the video tracks can be selected. In oneembodiment, a segment of the selected video track would be displayed inthe final video after the intro. The segment can be until the nextdecision point is reached i.e., a segment can correspond to a portion ofthe video track between decision points.

In some implementations, the selection can be made for multiple decisionpoints at the same time. For example, a particular video track may havemetadata that specifies that the next six segments are to be included inthe first segment is chosen from the video track. Thus, the decision isnot need to be made independently for all the decision points in themetadata, but only a plurality of them. Accordingly, at each of theplurality of decision points, the decision can be made as to whether tostay with the same video track or to change to a different video trackfor the final video.

The switch at a first decision point to a different video track can beto a different decision point, the one that corresponds to the firstdecision point. For example, the first decision point can correspond tothe start of the 7th push-up. However, the person can be performing atthe start of the 2^(nd) push-up in the video track that is being switchto. In this manner, control can be passed back and forth betweendecision points of the various video tracks and certain decision pointscan be reached more than once. At each decision point, the decision canbe made whether not to stay that the same video track or change to a newvideo track, in which corresponding time location in the new video trackis to be used.

The one or more selection rules include a total amount of repetitivemotion to be performed. As examples, the total amount can be a totalnumber of reps to be performed or total amount of time that therepetitive motion is to be performed. The total number of reps can beused in making the decisions at the decision points so that the finalvideo has the required number of reps. As part of the selection rules,the number of counts from one video track to another can be minimized.For example, the desired number of reps is 20, and the video tracksinclude a total of eight reps, then a minimum of two cuts between videotracks must be done.

Other selection rules can include positive and negative indicators.These indicators can be part of the metadata for a particular videotrack and can correspond to one or more decision points of the videotrack. A positive indicator can indicate a preference for using aparticular video track at one or more decision points. A negativeindicator can indicate disfavor for using a particular video track atone or more decision points (e.g., a segment of a video track can beblocked out). At some decision points, there can be no preference. Insuch a case, the selection rules can be used, which may includeselecting randomly or a video track not selected previously.

At block 1140, identification information of the selected segments issaved in a configuration file. The identification information can simplybe a timestamp (i.e., start time for when the selected video track isused) and a number corresponding to the selected video track. Theidentification information can include source track, destination track,insertion time, start time, and end time. The configuration file caninclude all of the information necessary to combine the video tracks tothe final video. The actual video tracks can be stored in other file(s).

At block 1150, the configuration file is provided to a video generationengine for combining the identified segments to obtain the exercisevideo. The video generation engine can be a hardware or software engine(or combination thereof) that is part of the computer system thatdetermine a configuration file. In another embodiment, the videogeneration engine is part of a different system. For example, the videogeneration engine can be on a user device and a server system cangenerate the configuration file. The client device can receive theconfiguration file and assemble the video tracks to form a video streamor a complete final video.

As the decision points can correspond to particular positions of theperson performing the motion, a switch from a first video track to asecond video track can be seamless. The person is at the same positionin the second video track as the person was just at in the first videotrack. Therefore, a judicious choice of decision points (along with asynchronization of the video) can allow any number of reps or durationto be displayed in the video.

C. Obtaining Video/Audio

The plurality of video tracks can be obtained from a multi-camera shootof a person performing the repetitive motion. Each camera can beshooting at a different angle. One camera angle can be a top-down view,a front view, either side view, or back view. The camera angles can alsochange as the cameras can move. In one embodiment, three or four videotracks are used

An introduction segment can also be obtained. For example, a coach canintroduce the move, e.g., a video the coach saying “okay now we're goingto do pushups.” There could be one or multiple versions of suchintroduction for a particular move. The same introduction can be usedfor multiple components that correspond to a same move. As part ofintroduction, a preview sequence can show the user what the user isabout to do, so the user can get ready for the exercise component.

The video charts can be of more than one person. One or more subjects(which may be human beings, computer-generated images, and or otherfigures, and hereinafter referred to as a “Model”) can be simultaneouslyrecorded from different angles by multiple video recording device. Inthe case of computer-generated images, it is rendered from multipleviewpoints. Other example camera angles can include: a wide angle viewof the scene, a close-up of certain body parts of the Model, afull-frame view of the Model, and dynamic viewpoints from two camerasthat move around the Model.

Certain embodiments may allow users to create customized videosthemselves, featuring video and audio (including music) content of theusers' choice. This feature allows for an even greater amount ofcustomization based on the needs and desires of the user. Users may beable to share such user-created videos with other users. For instance,User A may create a video for User B, who happens to be a longtimeworkout partner of User A. User B may be more motivated to engage inphysical activity with a customized video created by User A, based ontheir relationship. Additionally, users may rate and review videos, andsuch ratings and reviews could be made available to other users, to helpthem decide which video to choose from. The raw video of a selectedcoach, can then be used to assemble the customized video for the user'ssession.

D. Processing Data

The video and audio content that is recorded or generated as previouslydescribed can be arranged in a timeline in a computer software programto edit the video. The content from each video and audio recordingdevice may be shown as individual tracks in the program, and arrangedsuch that they are in sync with each other (i.e. when the content isplayed from within the software, all of the video and audio feeds playthe same moment in time from the original recording session, at the sametime). Certain parts of the video track marked out, e.g., when onecamera begins early in catches the Model walk out and getting inposition.

The content may be time-coded, using a feature such as chapter marking,to categorize or denote what is depicted. For example, a chapter marker(decision point) may be inserted at the beginning of the content todenote an introduction to the exercise by the Model. Another chaptermarker may be inserted at the transition point from the introductorysegment to the actual exercise. Additional chapter markers may beinserted at the beginning of each repetition of the exercise that followthe first one. And a chapter marker may be inserted at the end of thelast exercise repetition, to denote a transition point from the exerciseto an “outro” segment depicting the Model finishing the exercise.

Portions of the content may be flagged according to the desirability ofthe portions to be used in the final video. For instance, if the Modelmade a mistake during one of the exercise repetitions, the contentdepicting this flawed footage could be flagged as undesirable. Inanother example, one camera may move in front of another camera so thatfootage is not usable. Additionally, content depicting perfect formduring the exercise repetitions could be flagged as very desirable.

The content and added data such as chapter markers may be exported fromthe computer software to produce a lossless, high resolution video filewith audio, as well as a file that includes the added data, which may beencoded in XML format (Extensible Markup Language or other markuplanguage that defines a set of rules for encoding documents in a formatthat is both human-readable and machine-readable).

FIG. 12 shows a user interface 1200 of a video editing program that maybe used according to embodiments of the present invention. One or morevideo tracks 1210 can be processed according to a user's input. The usercan mark decision points 1220 in a video track. The metadata can includethe decision points and any other user input provided. The metadata canbe stored in metadata file, which may be stored separately from videotracks, but associated with the video tracks. Any of the information inthe metadata file can specify a particular time location in the videotrack that corresponds to the metadata being added (e.g., whether thetime location is good, bad, there should be used as a decision point).

Once the video tracks has been processed, an uploading tool can receivethe video tracks with the desired level(s) of video quality (e.g. 480 p,720, 1080 p) and the metadata file (e.g., a post-process XML file). Theuploading tool can upload them to a server, where the files can beaccessed to form a customized video. Thus, the metadata file can go intothe system and be associated with the move. The server knows that themove “pushups” has this file from the content server and know themetadata about what is inside the video file(s). The combination of thevideo file and the metadata file can be referred to as a media asset.The video editing interface (or different software) can also be used tocreate metadata for audio tracks.

FIG. 13A shows a diagram for meta-tagging audio corresponding to thevideo tracks according to embodiments of the present invention. Varioustags are added at different times and the audio track. In the exampleshown, a tag 1305 is added at a time location to indicate beats are tobe added to prepare the user for the start of the upcoming move. Tag1305 can be a required tag, as the beeps may be required.

Tag 1310 identifies a time location for a tip. Such a tag can specify aparticular time location or a range of time locations that can beacceptable. For example, certain parts of the audio track can be allowedto receive certain optional audio (e.g., tips) and other parts of theaudio track can be restricted from receiving optional audio.

Tag 1320 identifies a time location for an encouragement. Such a timelocation can be identified based on user feedback. For example, sensordata (e.g., a motion capture sensor) can identify that the user's motionfalls off at a certain point in previous sessions, and thus anencouragement can be inserted for next session. In a real-timeembodiment, the sensor data for the current session can be analyzed andthe encouragement can be added for the current session.

FIG. 13B shows a diagram 1350 of different video tracks and audio tracksaccording to embodiments of the present invention. This combination ofvideo and audio tracks can be packaged into a single media asset for aparticular move. Thus, each move can be bundled into a single file withseveral tracks. The meta-data about the layout of this file can be sentup to the server for use in online-editing. The video tracks can beproduced at multiple resolutions. The media asset can contain everythingneeded to play the move.

E. Selecting Media Assets

FIG. 14A shows a diagram of a media asset 1400 that can be used tocreate a customized video according to embodiments of the presentinvention. Media asset 1400 includes the video tracks audio tracks, aswell as metadata. The metadata includes decision points 1410. The mediaasset can be analyzed according to selection rules for a specificexercise session to provide a customized video for the exercise session.The selection rules can use information specific to the user for whichthe customized video is being generated.

FIG. 14B shows a diagram of the customized video 1450 according toembodiments of the present invention. Customized video 1450 correspondsto a destination timeline that the user sees. Customized video 1450 canbe created using a method 1100. The decision points 1410 and selectionrules can be used to determine which video tracks to use for the finalvideo track 1480.

A first segment 1461 of video 1480 is selected to be taken from videotrack 1. A second segment 1462 a video 1480 is selected to be taken fromvideo track 2. A third segment 1463 selected to be taken from videotrack 3. A fourth segment 1464 is selected to be taken from video track2. A fifth segment is selected to be taken from video track 3. And, asixth segment is selected to be taken from video track 1. The video 1480can be determined by performing multiple passes over the video tracks ofmedia asset 1400 to estimate the determination of which tracks to usefor each segments at the decision points.

As shown, the media asset is shorter than customized video 1450, asevidenced by a shorter timeline on the horizontal axis. Customized video1450 can be longer such as a combination of the video tracks. Differentparts of the video tracks can be placed at various points in video 1480to display any amount of the exercise motion.

The audio track can be assembled in a similar manner. In someembodiments, two or more audio tracks can be obtained. For example,audio track 1 can correspond to an audio track whose volume can bedecreased (silenceable). And, audio track 2 can correspond to an audiotrack was volume cannot be decreased (not silenceable). The segments ofthe audio tracks to not have to fill up the entire timeline, a certainparts of the timeline can be silent. The segments 1471-1478 correspondto different ones of audio tracks 1 and 2. These different audio trackscan correspond to video obtained from any of the cameras that obtain thevideo. The audio tracks can also include added audio, e.g., tips orencouragement, from stock files.

To assemble a customized video, the data may be manipulatedautomatically with the assistance of a microprocessor. Depending on whatdata is added in the previous steps (such as chapter markers) acustomized video may be assembled according to that added data. Forinstance, a customized video may be desired that shows an introduction(e.g., selected from one or more intros), a set of exercise repetitions,and an “outro” (e.g., selected for one or more outros). Certain data canbe extracted from the uploaded data, e.g. the chapter markers and theoriginal source camera for each edit. Using the chapter markers added inthe previous steps, a customized video can be assembled to show thosedesired portions. Content that is flagged as undesirable in previoussteps will not be available to be added to the customized video. Theexercise portions can be looped for desired length, and footage from thedifferent recording devices can be used to ensure seamless loopingrather than jerky cuts.

In one embodiment, the decision as to which video track to use at aparticular decision point (and potentially which part of the videotrack) can be performed using a weighted depth first search. A score canbe assigned to each of the video tracks, where the score predicts asuccess. The success can be measured by a quality of the destinationvideo track (e.g., as measured by metadata). Various time locationswithin the video track s can be given scores, so that the decision alsoincludes which point in the destination track is to be used.

The selection rules and the scores can account for how many more repsare to be performed. For example, the second to last rep of thedestination video track would not be selected for switching if 8 morereps are needed. Other selection rules can include a desire to getdifferent camera angles after a certain number of reps. As mentionedabove, the number of cuts can be minimized, so that when 50 reps areneeded and the video tracks have only 10 reps, one is not seeing thesame footage too much or being switched back and forth quickly. Inanother embodiment, the cuts (switch from one video track to another)can be made after a predetermined number of reps or predeterminedduration.

The decision can be broken down into different parts. For example, a cutcan be identified at a particular decision point. Then, whichdestination video track to use can be a separate decision. The decisionof the decision video track can account for the position of the currentcamera and a possible destination, and not use the possible destinationcamera of the two cameras are too close, as then the transition may notbe seamless.

F. Combining

Once the configuration file identifying the timelines for the customizedvideo is obtained, the configuration file can be used to create thecustomized video. The configuration file can identify the segments ofthe video tracks needed at particular times in the final timelines forthe customized video. Thus, the configuration file can provide theinstructions for assembling content and playing the customized video,e.g., seek to this time in this video track, play a particular segment,then seek to another location in another video track, and so on. Thus,the combination of the configuration file and the media asset (videotracks and audio) can provide the customized video.

This assembly process may also be done automatically with the assistanceof a processor. After the uploaded data reaches the server, ancustomized video can automatically be generated given certain built-inparameters that are designed with the desired end product in mind (e.g.a video with an introduction, exercise repetitions looped using thedesirable portions of the footage and cut from the different viewpointsof the various recording devices, and an outro).

The media asset can reside on servers, and the configuration file canreside on the user device or also on a server. The configuration filecan be generated in batch (e.g., at night) or in response to a userrequest. Once the configuration file is obtained, a final video can begenerated right away, or the configuration file can be saved for lateruse. The user can elect to generate the customized video using theconfiguration file for saving or for streaming.

G. Audio

Additionally, audio may be recorded during the video recording session,as well as in separate sessions during which no video is recorded, e.g.,utilizing a multi-track recording system. For instance, the coach'svoice may be recorded during a jumping jacks recording session.Additionally, the coach's voice may also be recorded on its own beforeor after the jumping jacks recording session. Timecode may or may not beapplied to audio recorded before, during, and or after the videorecording session

The audio may be time-coded similar to the video; a chapter marker maybe added to the instructional dialogue, to the counting of the exerciserepetitions, to exercise tips, encouragement, “outro” dialogue, etc.

Certain audio may be designated such that it will always play duringplayback (such as beeps that provide a cue for the user to stop andstart). Audio may be designated for toggling on and off by the userbefore or during playback (such as the Content Creator's voice). Also,certain audio clips that are categorized in a certain way may be easilyadded to the video in appropriate places. For example, an audio clip ofthe coach giving encouragement may be categorized as such, and thereforecan be easily added to the video in a spot where such encouragement maybe useful to the user (such as near the end of the exercise repetitions,or in response to feedback from the user that indicates the user isfalling behind in the exercise).

An example of where multiple tracks may be on the destination timelineis to allow users to adjust the volume of them independently. Inembodiment, a user can adjust the volume of the coaching independent ofthe audio queues (beeps, etc). A user can turn off or on different typesof audio. Some segments like beeps can be required, and volume can berestricted. Other audio can optionally be added, e.g., to say “goodjob”. Other audio includes tips (e.g., “keep your elbows straight”),encouragement (e.g., “keep going”, “don't stop now”), and jokes.Location specific audio can include a countdown.

The decision as to which audio to include at which points can be done atleast partially via an optimization technique. Different audio clips canhave different guidelines for selection rules. There can also beoverriding, tunable guidelines. For example, the ‘beep’ track can bedesignated as always backed up against the start and end of the move, soas to cue the user when to start and stop. A guideline can be that 40%(or other percentage) of the total time has audio, and/or a specificpercentage of coaching. Once the system fills in the required elements(beeps, instructions, etc), the system can fill in the remaining quota.Embodiments can maintain variety, randomization, and roughly equalspacing for remaining audio to be added.

Whether to include encouragement can be determined based on previoussession. For example, if the system knows that that the user has failedfor the last three sessions (or other number of sessions) just beforethe final rep, an encouragement can be added. If a component is donetwice in one session, then a different intro can be selected.

VI. Audio

In some embodiments, a custom sessions might only include audio.Embodiments described below can also be used in conjunction with acustom video. Embodiments can provide audio for any curriculum orprogram, e.g., weight lifting, running, yoga, physical therapy, etc.

A. Destination Timelines

FIG. 15 shows a diagram of the destination timeline 1500 including audioclips of various audio categories 1520 according to embodiments of thepresent invention. Destination timeline 1500 includes a plurality ofsegments 1561-1566. Destination timeline 1500 corresponds to audiocontent to be provided for an exercise session. The exercise session canbe a custom exercise session (e.g., as described herein) orpredetermined exercise session (e.g., that the user can select fromamong a plurality of existing exercise sessions). The exercise sessioncan include one or more exercise components.

Destination timeline 1500 corresponds to a single component of thesession. Additional destination timelines can be created for othercomponents. The destination timelines for the various components of thesession can be combined to obtain a destination timeline for the entiresession. Destination timeline 1500 can include configuration informationabout which audio clips are to be played at which time in the timeline.

As shown, the audio clips can be from a plurality of audio categories1520. In the example shown, audio categories 1520 include intros 1521,descriptions 1522, beeps 1523, jokes 1524, tips 1525, encouragements1526, and outros 1527. Other embodiments can include different audiocategories. The audio clips can have metadata that identifies to whichaudio category a particular audio clip corresponds.

Destination timeline 1500 includes a plurality of segments 1561-1566.Some of the segments can require audio, and one or more other segmentscan optionally have audio. In this example, segments 1561, 1562, 1563,1565, and 1565 are required segments, and segment 1564 can optionallyhave audio. Other embodiments can have more or less required segments.Destination timeline 1500 can correspond to an audio template that isselected for a particular component, session, or program. Differentcomponents of the same session can have different audio templates. Inaudio template can specify which segments are required and which onesare optional, as well as which categories can be used for whichsegments.

In some implementations, a particular audio category is assigned to aparticular segment. For example, segment 1561 is assigned to intros1521. Thus, an audio clip for segment 1561 is required to be selectedfrom audio clips corresponding to the category of intros 1521. In thisexample, segment 1564 can optionally include one or more audio clipsfrom one or more audio categories (jokes 1524, tips 1525, andencouragement 1526 as shown).

In one embodiment, a first pass is made through destination timeline1500. In the first pass, audio clips are selected for the requiredsegments. For example, segment 1561 can be identified as a requiredsegment can be assigned to intros 1521. Then, a particular audio clipcan be selected from the audio clips that have been tagged ascorresponding to intros 1521. In FIG. 15, intro #1 is selected.

Various selection rules can be used to determine which audio clip toselect. Such selection rules can include a preference for a variety, notto repeat an audio clip in a same session, and need as determined fromuser feedback. For the intros example, if push-ups have already beendone in the same session and the first intro audio clip stated “Are youready to do push-ups?”, then the second component for performingpush-ups can have an intro audio clip that states “Let's do push-upsagain?”.

In one embodiment, a score can be assigned to one or more of audio clipswithin a category. For example, every audio clip within a category canbe assigned to score (e.g., on factors described herein), and the audioclip with a high score can be selected. In other embodiments, a audioclip with a score above a threshold can be selected. The audio clips canbe assigned a score as they are tested, and the process can stop once anaudio clip is found with a sufficient score. This coarse the audio clipscan be specific to the particular destination timeline, and embodimentscan dynamically assign based on criteria specific to the particulardestination timeline.

In the first pass of this example, segment 1562 can be identified asrequiring an audio clip from descriptions 1522. According to selectionrules (which may be similar or different in the rules used for segment1561), description #6 is selected. The descriptions category candescribe the upcoming exercise to be performed. In one embodiment, thedescription can coincide with a video of a model performing theexercise.

Segment 1563 can be populated with an audio clip from beeps 1523. Thesebeeps can indicate to the user that the exercise is about to begin. Inone embodiment, beeps 1523 can also be used to indicate that theexercise is about to end. The beeps can also be used at periodic timesduring the exercise, e.g., to indicate when each rep of an exerciseshould be completed. The beeps can be at a prescribed cadence, which maybe determined as part of a custom exercise session. For example, thecadence can correspond to a particular user rank for the component.Segment 1566 corresponds to outros 1527.

Segment 1564 is shown as being able to accept audio clips fromcategories of jokes 1524, tips 1525, and encouragements 1526. Thus, asegment can receive more than one audio clip, and the audio clips can befrom more than one category, but can be from a same category. This isalso true for required segments. Tips can provide suggestions for how toperform an exercise, e.g., with good form. Encouragements can beprovided to encourage the user to complete an exercise. Other categoriesthat might be used for segment 1564 include other time information,e.g., “you're halfway there”.

Once a set of one or more audio clips has been selected, each audio clipcan be assigned to play at a particular time in destination timeline1500. Various methods can be used to determine when to play the audioclips. For example, the audio clips be specified to play with uniformspacing in between.

One criteria they can be used to select audio clips for an optionalsegment is a total amount of time that audio is to be played for thesegment. For example, it can be specified that audio is to be played 40%of the time (or about 40%+/−a cutoff). With such a criteria, the audioclips in the respective categories can be searched to identify one ormore suitable audio clips that satisfy this constraint (e.g., using aweighted depth first search). As a segments where just one audio clip ischosen, a score can be assigned to audio clips. Further, a score can beassigned to sets of audio clips. A set can be assembled and then a scorecan be assigned based on criteria described herein. Then, they can beascertained as to whether the score for the set is sufficient (e.g.,above a threshold).

The score for a particular audio clip a set of audio clips can bedetermined based on user feedback. For example, the user feedback canindicate that the user consistently fails the exercise at a particularpoint (e.g., at a particular rep or at a specific time). In this case,the score of a particular or any encouragement can increase as a result,e.g., such that an encouragement would be provided at a particular time.

As mentioned above, once the destination timeline for various componentsof a session have been completed, the destination timelines can becombined into a total destination timeline for the exercise session. Thetotal destination timeline can be saved as a configuration file, much ofthe same way the configuration file can be saved for a custom video.This configuration file can be sent to an audio generation engine forcreating the final audio content. As with the video, the audio can bestream percent is a file. And, the audio content can be generated on aserver or on a client device using the audio configuration file.

B. Method

FIG. 16 is a flowchart of a method 1600 of generating custom audiocontent for an exercise session according to embodiments of the presentinvention. As examples, the custom audio content can be an audio file oran audio stream. Method 1600 can be performed by a computer system,e.g., a same computer system that generates the configuration file forvideo.

At block 1610, data of a plurality of audio clips corresponding to aplurality of audio categories are received. The audio clips can benoises, voices, or any suitable audio. The audio clips can be taken ofvarious people. Each audio clip can be tagged with metadata identifyinga category to which the audio clip belongs.

At block 1620, metadata corresponding to the plurality of audio clipsare received. The metadata identifies an audio category for each audioclip. The data of the plurality of audio clips can be processed toobtain the metadata. The metadata for an audio clip can identify a lasttime that the audio clip was played in an exercise session for a user.

At block 1630, one or more components are identified for the exercisesession. Each component corresponds to a respective physical exercise.The components can be specified, e.g., using method 970. In otherembodiments, the user can select a predetermined session.

Blocks 1640-1670 are repeated for each component. A destination timelineof audio is created for each component. In some embodiments, the audioclips themselves are not needed and only the metadata and other data maybe used to determine a destination timeline.

At block 1640, one or more first segments of the destination timelinethat require audio are identified. Each first segment corresponds to anaudio category. In one embodiment, an audio template can be selected.The audio template can specify a duration for each of a plurality ofsegments of the destination timeline for a particular component. And,the audio template can specify which one or more segments are firstsegments and which one or more segments are second segments.

At block 1650, a first audio clip is selected from the correspondingaudio category for each first segment. The metadata is used to identifythe corresponding audio category. In one embodiment, the first audioclip can be selected based on a score. A score can be assigned to aplurality of audio clips of the corresponding category. Then, it can bedetermined that the first audio clip has a first score that satisfiesone or more criteria. In some implementations, a score can be determinedfor every audio clip and a top score can be selected.

At block 1660, one or more second segments of the destination timelinethat are optional for audio identified. In one embodiment, the one ormore second segments can be identified from an audio template. The audiotemplate can be in any suitable form such that the first and secondsegments can be identified.

At block 1670, one or more second audio clips are selected for the oneor more second segments based on one or more optional selection rules.In one embodiment, the one or more optional selection rules include oneor more criteria based on user feedback from a current session or aprevious session. For example, the user feedback can indicate that theuser fails at a particular point while performing a particularcomponent. A second audio clip can then correspond to an encouragementthat is selected to be played at the particular point. In anotherembodiment, the one or more optional selection rules can include a totaltime for audio during a second segment.

In one implementation, a set of the one or more second audio clips canbe selected for the one or more second segments based on a score for aset. A combined score can be determined for each of one or more possiblesets of one or more audio clips. Thus, a search can be performed ofvarious combination of audio clips to find a score that satisfies one ormore criteria (e.g., greater than a threshold).

At block 1680, identification information of the selected audio clips inthe identified segments of the one or more destination timelines issaved. The identification information is usable to generate the customaudio content. In one embodiment, the identification information (e.g.,as a configuration file) is provided to an audio generation engine forcombining the selected audio clips in the identified segments of the oneor more destination timeline to obtain the custom audio content. Theaudio generation engine (e.g., in the same computer system or adifferent one that determined the identification information) can thengenerate the custom audio content using the identification information.

VII. Other Functionality

Some embodiments can allow the user to make purchases from within theapplication, and deliver recommendations based on the data gathered by auser's use of the system. For instance, embodiments may recognize that auser is not regularly inputting their weight and may deliver anadvertisement, based on that insight, to the user for a WiFi enabledscale that automatically uploads weight to the system, via an API, everytime that user gets on it. The user may then purchase the scale fromwithin the application, or may follow a link to an outside service thatwill fulfill the order.

Some embodiments allow the user to engage with social networks to sharefitness related data. For instance, overweight users can easily connectwith other overweight users to share workout tips, customized workouts,and support for each other. The focus on social networking integrationwith certain embodiments may lead to greatly increased levels ofphysical activity for many users.

Certain embodiments may push users to engage in physical activity byissuing fitness challenges to them, based on the user's fitness level,preferences or other criteria. Challenges might be issued in response toa user request, at the direction of the system based on user feedback,based on a social goal (e.g. a group of users wants to collectively losea certain amount of weight), or based on an event occurring in theuser's area (e.g. the New York City Marathon). Digital badges can beearned by completing challenges and achieving milestones.

For example, a user lives in New York City wants to greatly improve theuser's long distance running ability, and indicates both facts to thesystem through manual input of data (or automatically, in the case ofuser location), may be challenged to run the New York City Marathon inthe year following the user's signing up for the service. Embodimentscould then deliver content to the user that would not only be customizedbased on user feedback (e.g. the user's performance as he engages incontent-specific activities), but also based on the overarching goal ofgetting the user to a position where he could run the New York CityMarathon. Other challenges might be on a smaller scale, such as having auser do 1,000 pushups in a week. For this challenge, the atomizedcontent delivered to the user would include enough pushup routines toallow the user to achieve this goal.

Certain embodiments may also prompt the user to engage health services.More specifically services can be connected to the system which mayfurther incentivize the user reaching the user's goals, by offeringincentives and rewards for user progress. For instance, a partner maydeliver an advertisement to the user through a program that offers theuser a discount on exercise apparel or health insurance, but which mayonly be redeemed if the user first completes a certain task or reach acertain goal in an exercise program. Users may consider such discountsand other rewards as being extra motivation to engage in physicalactivity.

VIII. Computer System

Any of the computer systems mentioned herein may utilize any suitablenumber of subsystems. Examples of such subsystems are shown in FIG. 17in computer apparatus 10. In some embodiments, a computer systemincludes a single computer apparatus, where the subsystems can be thecomponents of the computer apparatus. In other embodiments, a computersystem can include multiple computer apparatuses, each being asubsystem, with internal components.

The subsystems shown in FIG. 17 are interconnected via a system bus 75.Additional subsystems such as a printer 74, keyboard 78, storagedevice(s) 79, monitor 76, which is coupled to display adapter 82, andothers are shown. Peripherals and input/output (I/O) devices, whichcouple to I/O controller 71, can be connected to the computer system byany number of means known in the art, such as serial port 77. Forexample, serial port 77 or external interface 81 (e.g. Ethernet, Wi-Fi,etc.) can be used to connect computer system 10 to a wide area networksuch as the Internet, a mouse input device, or a scanner. Theinterconnection via system bus 75 allows the central processor 73 tocommunicate with each subsystem and to control the execution ofinstructions from system memory 72 or the storage device(s) 79 (e.g., afixed disk, such as a hard drive or optical disk), as well as theexchange of information between subsystems. The system memory 72 and/orthe storage device(s) 79 may embody a computer readable medium. Any ofthe data mentioned herein can be output from one component to anothercomponent and can be output to the user.

A computer system can include a plurality of the same components orsubsystems, e.g., connected together by external interface 81 or by aninternal interface. In some embodiments, computer systems, subsystem, orapparatuses can communicate over a network. In such instances, onecomputer can be considered a client and another computer a server, whereeach can be part of a same computer system. A client and a server caneach include multiple systems, subsystems, or components.

It should be understood that any of the embodiments of the presentinvention can be implemented in the form of control logic using hardware(e.g. an application specific integrated circuit or field programmablegate array) and/or using computer software with a generally programmableprocessor in a modular or integrated manner. As user herein, a processorincludes a multi-core processor on a same integrated chip, or multipleprocessing units on a single circuit board or networked. Based on thedisclosure and teachings provided herein, a person of ordinary skill inthe art will know and appreciate other ways and/or methods to implementembodiments of the present invention using hardware and a combination ofhardware and software.

Any of the software components or functions described in thisapplication may be implemented as software code to be executed by aprocessor using any suitable computer language such as, for example,Java, C, C++, C# or scripting language such as Perl or Python using, forexample, conventional or object-oriented techniques. The software codemay be stored as a series of instructions or commands on a computerreadable medium for storage and/or transmission, suitable media includerandom access memory (RAM), a read only memory (ROM), a magnetic mediumsuch as a hard-drive or a floppy disk, or an optical medium such as acompact disk (CD) or DVD (digital versatile disk), flash memory, and thelike. The computer readable medium may be any combination of suchstorage or transmission devices.

Such programs may also be encoded and transmitted using carrier signalsadapted for transmission via wired, optical, and/or wireless networksconforming to a variety of protocols, including the Internet. As such, acomputer readable medium according to an embodiment of the presentinvention may be created using a data signal encoded with such programs.Computer readable media encoded with the program code may be packagedwith a compatible device or provided separately from other devices(e.g., via Internet download). Any such computer readable medium mayreside on or within a single computer product (e.g. a hard drive, a CD,or an entire computer system), and may be present on or within differentcomputer products within a system or network. A computer system mayinclude a monitor, printer, or other suitable display for providing anyof the results mentioned herein to a user.

Any of the methods described herein may be totally or partiallyperformed with a computer system including one or more processors, whichcan be configured to perform the steps. Thus, embodiments can bedirected to computer systems configured to perform the steps of any ofthe methods described herein, potentially with different componentsperforming a respective steps or a respective group of steps. Althoughpresented as numbered steps, steps of methods herein can be performed ata same time or in a different order. Additionally, portions of thesesteps may be used with portions of other steps from other methods. Also,all or portions of a step may be optional. Additionally, any of thesteps of any of the methods can be performed with modules, circuits, orother means for performing these steps.

The specific details of particular embodiments may be combined in anysuitable manner without departing from the spirit and scope ofembodiments of the invention. However, other embodiments of theinvention may be directed to specific embodiments relating to eachindividual aspect, or specific combinations of these individual aspects.

The above description of exemplary embodiments of the invention has beenpresented for the purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdescribed, and many modifications and variations are possible in lightof the teaching above. The embodiments were chosen and described inorder to best explain the principles of the invention and its practicalapplications to thereby enable others skilled in the art to best utilizethe invention in various embodiments and with various modifications asare suited to the particular use contemplated.

A recitation of “a”, “an” or “the” is intended to mean “one or more”unless specifically indicated to the contrary.

All patents, patent applications, publications, and descriptionsmentioned here are incorporated by reference in their entirety for allpurposes. None is admitted to be prior art.

What is claimed is:
 1. A method of generating a customized exercisevideo for a user, the method being implemented by (i) a computer systemcomprising one or more processors and (ii) a wearable sensor devicecomprising one or more sensors, the method comprising: (a) identifying aplurality of components, each component corresponding to a respectivephysical exercise and associated with one of a plurality of categories;(b) assigning a difficulty rank to each component, wherein assigning thedifficulty rank to an instant component includes: receiving user ranksfor a plurality of prior users that have performed the instantcomponent, receiving user feedback from the plurality of prior usersabout performing the instant component, and setting the difficulty rankof the instant component based on the user feedback from the pluralityof prior users and the user ranks for the plurality of prior users; (c)determining, by the computer system and for each category in theplurality of categories, a category user rank for the user; (d)identifying, by the computer system and for each of the plurality ofcategories, a respective set of components in the plurality ofcomponents having a difficulty rank within a specified range of thecategory user rank as being available; (e) generating, by the computersystem, the customized exercise video including an exercise sessioncomposed of a plurality of available components identified in (d); (f)displaying the customized exercise video to the user; (g) receiving, bythe computer system, sensor data of the user from the wearable sensordevice, wherein the sensor data of the user are generated by the one ormore sensors of the wearable sensor device when the user is wearing thewearable sensor device, and wherein the sensor data of the user indicatethe user's performance of, or the user's physiological condition during,a physical exercise of the customized exercise video; and (h) modifying,during playback of the customized exercise video and by the computersystem, the content of the customized exercise video based on the sensordata of the user by performing an action selected from the groupconsisting of: (a) changing an amount of a physical exercise of aparticular component of the plurality of available components, (b)adding to the customized exercise video a new component having adifficulty rank different from that of the particular component of theplurality of available components, (c) adding to the customized exercisevideo a new coaching audio clip not initially included in the customizedexercise video, and (d) any combination thereof.
 2. The method of claim1, wherein determining the category user rank comprises: receiving aninitial user rank; receiving instant user feedback about a firstcomponent that the user has performed, the first component having afirst difficulty rank; and changing the initial user rank based on theinstant user feedback, the initial user rank, and the first difficultyrank.
 3. The method of claim 2, further comprising: calculating apredicted score for the user against the first component based on theinitial user rank and the first difficulty rank; calculating a userscore for the user against the first component based on the instant userfeedback; and comparing the predicted score to the user score todetermine a change in the initial user rank.
 4. The method of claim 3,further comprising: determining a winning stake and a losing stake basedon the initial user rank and the first difficulty rank; and calculatingan outcome score that specifies a percentage of the winning stake or thelosing stake to use in changing the initial user rank.
 5. The method ofclaim 1, wherein the user feedback includes a level of completion of oneor more components.
 6. The method of claim 1, wherein the user feedbackincludes responses to a questionnaire.
 7. The method of claim 1, whereinthe user feedback includes sensor data from a device that measures aphysiological condition and/or a body motion of the plurality of priorusers.
 8. The method of claim 7, wherein the sensor data were obtainedwhile the plurality of prior users were performing a component.
 9. Themethod of claim 1, wherein the plurality of categories correspond todifferent parts of a body.
 10. The method of claim 1, wherein thecomponents in the exercise session are arranged in a particular order.11. The method of claim 1, wherein the specified range for a firstcategory is offset from the category user rank.
 12. The method of claim1, wherein assigning the difficulty rank to each component occurs priorto receiving a request to generate the customized exercise video. 13.The method of claim 1, wherein generating the customized exercise videocomprises generating a video file.
 14. The method of claim 13, whereindisplaying the customized exercise video to the user comprises sendingthe video file by a video server over a network to a client device andplaying back the video file to display the customized exercise video onthe client device.
 15. A computer product comprising a non-transitorycomputer readable medium storing a plurality of instructions that whenexecuted control a computer system to generate a customized exercisevideo for a user, the instructions comprising: (a) identifying aplurality of components, each component corresponding to a respectivephysical exercise and associated with one of a plurality of categories;(b) assigning a difficulty rank to each component, wherein assigning thedifficulty rank to an instant component includes: receiving user ranksfor a plurality of prior users that have performed the instantcomponent, receiving user feedback from the plurality of prior usersabout performing the instant component, and setting the difficulty rankof the instant component based on the user feedback from the pluralityof prior users and the user ranks for the plurality of prior users; (c)determining, for each category in the plurality of categories, acategory user rank for the user; (d) identifying, for each of theplurality of categories, a respective set of components in the pluralityof components having a difficulty rank within a specified range of thecategory user rank as being available; (e) generating the customizedexercise video including an exercise session composed of a plurality ofavailable components identified in (d); and (f) displaying thecustomized exercise video to the user; (g) receiving sensor data of theuser from a wearable sensor device, wherein the sensor data of the userare generated by one or more sensors of the wearable sensor device whenthe user is wearing the wearable sensor device, and wherein the sensordata of the user indicate the user's performance of, or the user'sphysiological condition during, a physical exercise of the customizedexercise video; and (h) modifying, during the playback of the customizedexercise video, the content of the customized exercise video based onthe sensor data of the user by performing an action selected from thegroup consisting of: (a) changing an amount of a physical exercise of aparticular component of the plurality of available components, (b)adding to the customized exercise video a new component having adifficulty rank different from that of the particular component of theplurality of available components, (c) adding to the customized exercisevideo a new coaching audio clip not initially included in the customizedexercise video, and (d) any combination thereof.
 16. The computerproduct of claim 15, wherein determining the category user rankcomprises: receiving an initial user rank; receiving instant userfeedback about a first component that the user has performed, the firstcomponent having a first difficulty rank; and changing the initial userrank based on the instant user feedback, the initial user rank, and thefirst difficulty rank.
 17. The computer product of claim 16, wherein theinstructions further comprise: calculating a predicted score for theuser against the first component based on the initial user rank and thefirst difficulty rank; calculating a user score for the user against thefirst component based on the instant user feedback; and comparing thepredicted score to the user score to determine a change in the initialuser rank.
 18. The computer product of claim 17, wherein theinstructions further comprise: determining a winning stake and a losingstake based on the initial user rank and the first difficulty rank; andcalculating an outcome score that specifies a percentage of the winningstake or the losing stake to use in changing the initial user rank. 19.The computer product of claim 15, wherein the user feedback includes alevel of completion of one or more components.
 20. The computer productof claim 15, wherein the user feedback includes sensor data from adevice that measures a physiological condition and/or a body motion ofthe plurality of prior users.
 21. The computer product of claim 15,wherein the specified range for a first category is offset from thecategory user rank.